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Communication Dans Un Congrès Année : 2013

On the use of a mixed binary join tree for exact inference in dynamic directed evidential networks with conditional belief functions

Résumé

Dynamic directed evidential network with conditional belief functions (DDEVN) is a framework for reasoning under uncertainty over systems evolving in time. Based on the theory of belief function, the DDEVN allows to faithfully represent various forms of uncertainty. In this paper, we propose a new algorithm for inference in DDEVNs. We especially present a computational structure, namely the mixed binary join tree, which is appropriate for the exact inference in these networks.

Dates et versions

hal-00933109 , version 1 (19-01-2014)

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Citer

Wafa Laâmari, Boutheina Ben Yaghlane, Christophe Simon. On the use of a mixed binary join tree for exact inference in dynamic directed evidential networks with conditional belief functions. 6th International Conference on Knowledge Science, Engineering and Management, KSEM 2013, Aug 2013, Dalian, China. pp.CDROM, ⟨10.1007/978-3-642-39787-5_26⟩. ⟨hal-00933109⟩
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